What Kind of Career Can I Get If I Am a Data Science Major?

Data sci­ence is an incred­i­bly diverse data-dri­ven field. It is the com­bi­na­tion of sev­er­al dif­fer­ent dis­ci­plines such as sta­tis­tics, data analy­sis, machine learn­ing, and com­put­er sci­ence. Because of the broad scope of data sci­ence, there are jobs in the field across the board; you can work in busi­ness, finance, foren­sics, or even in med­ical. Glass­door has rat­ed data sci­ence jobs as the top in Amer­i­ca, and it is the third year in a row that it has assert­ed this because it is grow­ing expo­nen­tial­ly each year, pays well, and allows some­one to work close­ly in an area they are pas­sion­ate about in a tech-cen­tric way that has­n’t always been avail­able in the past.

The amount of career oppor­tu­ni­ties when you are a data sci­ence major are vir­tu­al­ly end­less. IBM pre­dicts that the demand for data sci­en­tists will increase 28% from 2017 to 2020; McK­in­sey & Co. report­ed that in 2018 there are near­ly 500,000 data sci­ence jobs with only 200,000 qual­i­fied indi­vid­u­als avail­able. As peo­ple con­tin­ue to cre­ate data, more peo­ple will be required to process it all.

There are options in account­ing, busi­ness, defense, foren­sics, archi­tec­ture, con­struc­tion, con­sumer elec­tron­ics, phar­ma­ceu­ti­cals, enter­tain­ment, health­care, and more. In any of these indus­tries, there is a need to col­lect and process infor­ma­tion on a larg­er scale, so those who are trained in data sci­ence can flour­ish with­in them.

Many schools offer data sci­ence pro­grams along­side busi­ness pro­grams or even con­cen­tra­tions in crim­i­nal jus­tice or health­care admin­is­tra­tion. It is gen­er­al­ly con­sid­ered that there are four types of careers in data sci­ence: ana­lysts, engi­neers, sta­tis­ti­cians, and intel­li­gence reporters.

Ana­lysts are tasked with mar­ket research, or scru­ti­niz­ing data col­lect­ed by a com­pa­ny and mak­ing pro­jec­tions based on that. In addi­tion, you will have to com­pose and report your find­ings in a way that is mean­ing­ful to the com­pa­ny. As an exam­ple, if you work for a cloth­ing com­pa­ny, you would have to look at shop­ping pat­terns and be able to project what sea­son a par­tic­u­lar item might per­form best in.

This is sim­i­lar to intel­li­gence reporters, who will col­lect data and report it to their employ­ers. How­ev­er, intel­li­gence reporters will not go as in-depth with the research that they con­duct and will not have to make as many detailed projections.

Sta­tis­ti­cians will have to use the infor­ma­tion col­lect­ed by their employ­ers to cre­ate sta­tis­tics, as well as ana­lyze exist­ing sta­tis­tics to cre­ate rel­e­vant reports. Usu­al­ly, gov­ern­ment agen­cies, author­i­ties, and mar­ket research com­pa­nies are some places you would fit in as a sta­tis­ti­cian. Engi­neers are respon­si­ble for the soft­ware behind the scenes, cre­at­ing and main­tain­ing soft­ware to col­lect and orga­nize the data. This is also some­times called data min­ing and requires exten­sive knowl­edge of script­ing and programming.

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